{"title":"基于关联传播和蚁群优化的超链接环境下搜索个性化","authors":"P. Krömer, V. Snás̃el, J. Platoš, S. Owais","doi":"10.1109/HIS.2010.5600017","DOIUrl":null,"url":null,"abstract":"Personalization is a promising way of improvement of the search services in large document collections and on the Web. User modeling is in the core of many personalization efforts because accurate user model can provide essential information for user specific search adjustments and result set processing. In this paper, we propose and study user modeling technique based on click-through data, relevance propagation and ant colony optimization.","PeriodicalId":174618,"journal":{"name":"2010 10th International Conference on Hybrid Intelligent Systems","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Search personalization in hyperlinked environments by relevance propagation and ant colony optimization\",\"authors\":\"P. Krömer, V. Snás̃el, J. Platoš, S. Owais\",\"doi\":\"10.1109/HIS.2010.5600017\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Personalization is a promising way of improvement of the search services in large document collections and on the Web. User modeling is in the core of many personalization efforts because accurate user model can provide essential information for user specific search adjustments and result set processing. In this paper, we propose and study user modeling technique based on click-through data, relevance propagation and ant colony optimization.\",\"PeriodicalId\":174618,\"journal\":{\"name\":\"2010 10th International Conference on Hybrid Intelligent Systems\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 10th International Conference on Hybrid Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HIS.2010.5600017\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 10th International Conference on Hybrid Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HIS.2010.5600017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Search personalization in hyperlinked environments by relevance propagation and ant colony optimization
Personalization is a promising way of improvement of the search services in large document collections and on the Web. User modeling is in the core of many personalization efforts because accurate user model can provide essential information for user specific search adjustments and result set processing. In this paper, we propose and study user modeling technique based on click-through data, relevance propagation and ant colony optimization.